Multiplayer Tension in the Wild: A Hearthstone Case

Paris Mavromoustakos-Blom, Dávid Melhárt, Antonios Liapis, Georgios N. Yannakakis, Sander Bakkes, Pieter Spronck

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


Games are designed to elicit strong emotions during game play, especially when players are competing against each other. Artificial Intelligence applied to predict a player's emotions has mainly been tested on single-player experiences in low-stakes settings and short-term interactions. How do players experience and manifest affect in high-stakes competitions, and which modalities can capture this? This paper reports a first experiment in this line of research, using a competition of the video game Hearthstone where both competing players' game play and facial expressions were recorded over the course of the entire match which could span up to 41 minutes. Using two experts' annotations of tension using a continuous video affect annotation tool, we attempt to predict tension from the webcam footage of the players alone. Treating both the input and the tension output in a relative fashion, our best models reach 66.3% average accuracy (up to 79.2% at the best fold) in the challenging leave-one-participant out cross-validation task. This initial experiment shows a way forward for affect annotation in games "in the wild"in high-stakes, real-world competitive settings.

Original languageEnglish
Title of host publicationProceedings of the 18th International Conference on the Foundations of Digital Games, FDG 2023
EditorsPhil Lopes, Filipe Luz, Antonios Liapis, Henrik Engstrom
PublisherAssociation for Computing Machinery (ACM)
ISBN (Electronic)9781450398565
ISBN (Print)9781450398558
Publication statusPublished - 12 Apr 2023
Event18th International Conference on the Foundations of Digital Games, FDG 2023 - Lisbon, Portugal
Duration: 11 Apr 202314 Apr 2023

Publication series

NameACM International Conference Proceeding Series


Conference18th International Conference on the Foundations of Digital Games, FDG 2023


  • competitive games
  • facial expression analysis
  • Player affect
  • player modeling


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